1. Field of the Invention
This invention relates generally to the estimation of the system transfer function for certain linear systems, for example the estimation of the pupil image function matrix for plenoptic imaging systems.
2. Description of the Related Art
As an example of one class of systems, the plenoptic imaging system has recently received increased attention. It can be used to recalculate a different focus point or point of view of an object, based on digital processing of the captured plenoptic image. The plenoptic imaging system also finds application in multi-modal imaging, using a multi-modal filter array in the plane of the pupil aperture. Each filter is imaged at the sensor, effectively producing a multiplexed image of the object for each imaging modality at the filter plane. Other applications for plenoptic imaging systems include varying depth of field imaging and high dynamic range imaging.
Many of these applications depend strongly on an accurate characterization of the plenoptic imaging system. This is especially true for applications that utilize more advanced image processing, such as deconvolution and super-resolution. For example, if the point response of a plenoptic imaging system can be accurately estimated, then an inverse problem can be solved to obtain higher resolution images from the captured plenoptic images.
The behavior of a plenoptic imaging system can be calculated based on the design data for the system. However, the physical system will deviate from the design data and even small deviations can affect the overall performance of the system. For example, the use of micro-elements, such as microlens arrays, increases the sensitivity to deviations and imposes a stricter requirement on the characterization of the plenoptic imaging system. Thus, calibration of physical systems, rather than modeling based on design data, is desirable in certain situations.
The point response for a plenoptic imaging system will be referred to as the “pupil image function” (PIF) of the plenoptic imaging system, as described in more detail below. Unlike conventional optical imaging systems, the PIF for a plenoptic imaging system is strongly spatially variant. Therefore, the PIF cannot be estimated for only a single field point, with the assumption that the PIF will then be the same or similar for all other field points. Rather, the PIF preferably is estimated over the entire field of view of the plenoptic imaging system. In one approach, a point source object is physically translated across the entire field of view, and the system's response is observed separately at each field point. The PIF is then assembled from the observed images. However, this approach is very time consuming.
Thus, there is a need for better methods for estimating the PIF of a plenoptic imaging system and, more generally, for estimating the system transfer function for a certain class of linear systems.